{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c4f29d4c-0c46-48e2-905a-20f2235a18ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from pathlib import Path\n",
    "\n",
    "from scripts.continual_learning.attr_definitions import AGGREGATE_ATTRS, NONAGGREGATE_ATTRS\n",
    "\n",
    "output_folder = Path(\"../data/continual_mitigation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ea7e228b-18ef-4b9f-b46f-7a08b080189f",
   "metadata": {},
   "outputs": [],
   "source": [
    "wilds = pd.read_csv(output_folder / \"civilcomments_wilds_v1.0/all_data_with_identities.csv\", index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bfa6e091-84e8-4d82-941b-f2f2cc942089",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>test</th>\n",
       "      <td>16327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>train</th>\n",
       "      <td>34120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>val</th>\n",
       "      <td>5423</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id\n",
       "split       \n",
       "test   16327\n",
       "train  34120\n",
       "val     5423"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Multiple identity mentions\n",
    "wilds.query(\"more_than_one_identity == True\").groupby(\"split\")[[\"id\"]].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d827e3fb-e588-45d9-8ae5-4f2547d692c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>test</th>\n",
       "      <td>55346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>train</th>\n",
       "      <td>113470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>val</th>\n",
       "      <td>18847</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id\n",
       "split        \n",
       "test    55346\n",
       "train  113470\n",
       "val     18847"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# At least 1 identity mention\n",
    "wilds.query(\"identity_any == 1\").groupby(\"split\")[[\"id\"]].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2d368a8d-70e2-48bf-8ffb-ddae3ea87ae5",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>test</th>\n",
       "      <td>39019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>train</th>\n",
       "      <td>79350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>val</th>\n",
       "      <td>13424</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          id\n",
       "split       \n",
       "test   39019\n",
       "train  79350\n",
       "val    13424"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Only 1 identity mention\n",
    "wilds.query(\"identity_any == 1 and more_than_one_identity == False\").groupby(\"split\")[[\"id\"]].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5e3d8c79-f1d2-462d-8a4f-f5c27113daf3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>test</th>\n",
       "      <td>78436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>train</th>\n",
       "      <td>155568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>val</th>\n",
       "      <td>26333</td>\n",
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       "  </tbody>\n",
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      "text/plain": [
       "           id\n",
       "split        \n",
       "test    78436\n",
       "train  155568\n",
       "val     26333"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Zero identity mentions\n",
    "wilds.query(\"identity_any == 0\").groupby(\"split\")[[\"id\"]].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "24f1b61d-02f3-4b22-93de-73ccab77328d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'comment_text', 'split', 'created_date', 'publication_id',\n",
       "       'parent_id', 'article_id', 'rating', 'funny', 'wow', 'sad', 'likes',\n",
       "       'disagree', 'toxicity', 'severe_toxicity', 'obscene', 'sexual_explicit',\n",
       "       'identity_attack', 'insult', 'threat', 'male', 'female', 'transgender',\n",
       "       'other_gender', 'heterosexual', 'homosexual_gay_or_lesbian', 'bisexual',\n",
       "       'other_sexual_orientation', 'christian', 'jewish', 'muslim', 'hindu',\n",
       "       'buddhist', 'atheist', 'other_religion', 'black', 'white', 'asian',\n",
       "       'latino', 'other_race_or_ethnicity', 'physical_disability',\n",
       "       'intellectual_or_learning_disability', 'psychiatric_or_mental_illness',\n",
       "       'other_disability', 'identity_annotator_count',\n",
       "       'toxicity_annotator_count', 'LGBTQ', 'other_religions',\n",
       "       'asian_latino_etc', 'disability_any', 'identity_any', 'num_identities',\n",
       "       'more_than_one_identity', 'na_gender', 'na_orientation', 'na_religion',\n",
       "       'na_race', 'na_disability'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wilds.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9d8db8a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial shape: (131793, 59)\n",
      "Dataframe contains only instances with a single domain.\n",
      "Domains (10): LGBTQ, other_religions, asian_latino_etc, disability_any, male, female, christian, muslim, white, black\n",
      "Number of instances without a domain (removed): 173\n",
      "Number of instances with a single domain (kept): 131620\n",
      "Final shape: (131620, 60)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "train    92647\n",
       "test     38973\n",
       "Name: split, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>LGBTQ</th>\n",
       "      <th>other_religions</th>\n",
       "      <th>asian_latino_etc</th>\n",
       "      <th>disability_any</th>\n",
       "      <th>male</th>\n",
       "      <th>female</th>\n",
       "      <th>christian</th>\n",
       "      <th>muslim</th>\n",
       "      <th>white</th>\n",
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       "    <tr>\n",
       "      <th>split</th>\n",
       "      <th>toxic</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">test</th>\n",
       "      <th>0</th>\n",
       "      <td>1542</td>\n",
       "      <td>1391</td>\n",
       "      <td>1205</td>\n",
       "      <td>1119</td>\n",
       "      <td>4884</td>\n",
       "      <td>7408</td>\n",
       "      <td>8263</td>\n",
       "      <td>3261</td>\n",
       "      <td>2685</td>\n",
       "      <td>1306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>514</td>\n",
       "      <td>181</td>\n",
       "      <td>124</td>\n",
       "      <td>264</td>\n",
       "      <td>739</td>\n",
       "      <td>1103</td>\n",
       "      <td>571</td>\n",
       "      <td>867</td>\n",
       "      <td>928</td>\n",
       "      <td>618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">train</th>\n",
       "      <th>0</th>\n",
       "      <td>3439</td>\n",
       "      <td>2859</td>\n",
       "      <td>2712</td>\n",
       "      <td>2459</td>\n",
       "      <td>11347</td>\n",
       "      <td>19097</td>\n",
       "      <td>19269</td>\n",
       "      <td>7645</td>\n",
       "      <td>6701</td>\n",
       "      <td>3167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1127</td>\n",
       "      <td>405</td>\n",
       "      <td>316</td>\n",
       "      <td>600</td>\n",
       "      <td>1619</td>\n",
       "      <td>2760</td>\n",
       "      <td>1281</td>\n",
       "      <td>2046</td>\n",
       "      <td>2438</td>\n",
       "      <td>1360</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             LGBTQ  other_religions  asian_latino_etc  disability_any   male  \\\n",
       "split toxic                                                                    \n",
       "test  0       1542             1391              1205            1119   4884   \n",
       "      1        514              181               124             264    739   \n",
       "train 0       3439             2859              2712            2459  11347   \n",
       "      1       1127              405               316             600   1619   \n",
       "\n",
       "             female  christian  muslim  white  black  \n",
       "split toxic                                           \n",
       "test  0        7408       8263    3261   2685   1306  \n",
       "      1        1103        571     867    928    618  \n",
       "train 0       19097      19269    7645   6701   3167  \n",
       "      1        2760       1281    2046   2438   1360  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "domains = list(AGGREGATE_ATTRS.keys()) + list(NONAGGREGATE_ATTRS.keys())\n",
    "domains.remove(\"identity_any\")\n",
    "\n",
    "wilds_identity = wilds.query(\"identity_any == 1 and more_than_one_identity == False\").copy()\n",
    "wilds_identity[\"toxic\"] = (wilds_identity[\"toxicity\"] >= 0.5).astype(int)\n",
    "print(f\"Initial shape: {wilds_identity.shape}\")\n",
    "\n",
    "for domain in NONAGGREGATE_ATTRS.keys():\n",
    "    wilds_identity[domain] = (wilds_identity[domain] >= 0.5).astype(int)\n",
    "\n",
    "no_attr = wilds_identity[domains].sum(axis=1) == 0\n",
    "single_attr = wilds_identity[domains].sum(axis=1) == 1\n",
    "wilds_identity = wilds_identity[~no_attr]\n",
    "\n",
    "# Add domain column\n",
    "wilds_identity[\"domain\"] = wilds_identity[domains].apply(lambda x: x[x == 1].index[0], axis=1)\n",
    "# Merge train and validation splits\n",
    "wilds_identity[\"split\"] = wilds_identity[\"split\"].map({\"train\": \"train\", \"val\": \"train\", \"test\": \"test\"})\n",
    "\n",
    "if single_attr.sum() != wilds_identity.shape[0]:\n",
    "    raise ValueError(\"Dataframe contains instances with multiple domains.\")\n",
    "else:\n",
    "    print(\"Dataframe contains only instances with a single domain.\")\n",
    "\n",
    "print(f\"Domains ({len(domains)}): {', '.join(domains)}\")\n",
    "print(f\"Number of instances without a domain (removed): {no_attr.sum()}\")\n",
    "print(f\"Number of instances with a single domain (kept): {single_attr.sum()}\")\n",
    "print(f\"Final shape: {wilds_identity.shape}\")\n",
    "\n",
    "display(wilds_identity['split'].value_counts())\n",
    "display(wilds_identity.groupby([\"split\", \"toxic\"])[domains].sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "30955603",
   "metadata": {},
   "outputs": [
    {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>domain</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>asian_latino_etc</th>\n",
       "      <td>4357.0</td>\n",
       "      <td>0.130</td>\n",
       "      <td>0.205</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.200</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>disability_any</th>\n",
       "      <td>4442.0</td>\n",
       "      <td>0.212</td>\n",
       "      <td>0.255</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.167</td>\n",
       "      <td>0.400</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other_religions</th>\n",
       "      <td>4836.0</td>\n",
       "      <td>0.175</td>\n",
       "      <td>0.213</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.167</td>\n",
       "      <td>0.300</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>black</th>\n",
       "      <td>6451.0</td>\n",
       "      <td>0.314</td>\n",
       "      <td>0.259</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.300</td>\n",
       "      <td>0.500</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LGBTQ</th>\n",
       "      <td>6622.0</td>\n",
       "      <td>0.278</td>\n",
       "      <td>0.246</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.200</td>\n",
       "      <td>0.473</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>white</th>\n",
       "      <td>12752.0</td>\n",
       "      <td>0.292</td>\n",
       "      <td>0.246</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.300</td>\n",
       "      <td>0.500</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>muslim</th>\n",
       "      <td>13819.0</td>\n",
       "      <td>0.249</td>\n",
       "      <td>0.243</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.200</td>\n",
       "      <td>0.400</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>18589.0</td>\n",
       "      <td>0.150</td>\n",
       "      <td>0.230</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.200</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>christian</th>\n",
       "      <td>29384.0</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.175</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.167</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>female</th>\n",
       "      <td>30368.0</td>\n",
       "      <td>0.159</td>\n",
       "      <td>0.224</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.200</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    count   mean    std  min  25%    50%    75%  max\n",
       "domain                                                              \n",
       "asian_latino_etc   4357.0  0.130  0.205  0.0  0.0  0.000  0.200  1.0\n",
       "disability_any     4442.0  0.212  0.255  0.0  0.0  0.167  0.400  1.0\n",
       "other_religions    4836.0  0.175  0.213  0.0  0.0  0.167  0.300  1.0\n",
       "black              6451.0  0.314  0.259  0.0  0.0  0.300  0.500  1.0\n",
       "LGBTQ              6622.0  0.278  0.246  0.0  0.0  0.200  0.473  1.0\n",
       "white             12752.0  0.292  0.246  0.0  0.0  0.300  0.500  1.0\n",
       "muslim            13819.0  0.249  0.243  0.0  0.0  0.200  0.400  1.0\n",
       "male              18589.0  0.150  0.230  0.0  0.0  0.000  0.200  1.0\n",
       "christian         29384.0  0.105  0.175  0.0  0.0  0.000  0.167  1.0\n",
       "female            30368.0  0.159  0.224  0.0  0.0  0.000  0.200  1.0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wilds_identity.groupby(\"domain\")[\"toxicity\"].describe().sort_values(by=\"count\").round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2b525ade",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>comment_text</th>\n",
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       "      <th>0</th>\n",
       "      <td>627762</td>\n",
       "      <td>OH yes - Were those evil Christian Missionarie...</td>\n",
       "      <td>test</td>\n",
       "      <td>2016-11-26 15:56:03.862109+00</td>\n",
       "      <td>13</td>\n",
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       "      <th>2</th>\n",
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       "      <td>even up here.......BLACKS!</td>\n",
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       "      <td>2016-08-04 16:48:07.175252+00</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>7122949</td>\n",
       "      <td>Lela, you admit no records exist to support yo...</td>\n",
       "      <td>test</td>\n",
       "      <td>2017-06-09 05:12:03.477137+00</td>\n",
       "      <td>21</td>\n",
       "      <td>5373513.0</td>\n",
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       "      <th>17</th>\n",
       "      <td>5621001</td>\n",
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       "      <td>test</td>\n",
       "      <td>2017-07-19 16:48:17.442622+00</td>\n",
       "      <td>53</td>\n",
       "      <td>5620646.0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <th>447991</th>\n",
       "      <td>5533327</td>\n",
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       "      <td>train</td>\n",
       "      <td>2017-07-05 17:58:11.764575+00</td>\n",
       "      <td>102</td>\n",
       "      <td>NaN</td>\n",
       "      <td>351854</td>\n",
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       "    <tr>\n",
       "      <th>447992</th>\n",
       "      <td>784202</td>\n",
       "      <td>Charles has a serious victim mentality disorder.</td>\n",
       "      <td>train</td>\n",
       "      <td>2017-01-03 18:08:33.913588+00</td>\n",
       "      <td>13</td>\n",
       "      <td>776014.0</td>\n",
       "      <td>159306</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447994</th>\n",
       "      <td>6212478</td>\n",
       "      <td>Neither are gays a \"protected class of citizen...</td>\n",
       "      <td>train</td>\n",
       "      <td>2017-10-24 15:35:13.755758+00</td>\n",
       "      <td>102</td>\n",
       "      <td>6209282.0</td>\n",
       "      <td>392544</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447998</th>\n",
       "      <td>5165492</td>\n",
       "      <td>I just don't find her a very good representati...</td>\n",
       "      <td>train</td>\n",
       "      <td>2017-04-22 18:42:02.442987+00</td>\n",
       "      <td>54</td>\n",
       "      <td>NaN</td>\n",
       "      <td>328877</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>447999</th>\n",
       "      <td>4984105</td>\n",
       "      <td>You know the Trump fanatics are trolling the G...</td>\n",
       "      <td>train</td>\n",
       "      <td>2017-03-10 00:55:35.369198+00</td>\n",
       "      <td>54</td>\n",
       "      <td>807615.0</td>\n",
       "      <td>156960</td>\n",
       "      <td>0.400000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>131620 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id                                       comment_text  split  \\\n",
       "0        627762  OH yes - Were those evil Christian Missionarie...   test   \n",
       "2        416437                         even up here.......BLACKS!  train   \n",
       "4        855753  And the woman exposing herself saying grab thi...  train   \n",
       "11      7122949  Lela, you admit no records exist to support yo...   test   \n",
       "17      5621001  Ridiculous, indeed. Although Rome does seem to...   test   \n",
       "...         ...                                                ...    ...   \n",
       "447991  5533327  \"Match found that 91 percent of liberals say t...  train   \n",
       "447992   784202   Charles has a serious victim mentality disorder.  train   \n",
       "447994  6212478  Neither are gays a \"protected class of citizen...  train   \n",
       "447998  5165492  I just don't find her a very good representati...  train   \n",
       "447999  4984105  You know the Trump fanatics are trolling the G...  train   \n",
       "\n",
       "                         created_date  publication_id  parent_id  article_id  \\\n",
       "0       2016-11-26 15:56:03.862109+00              13   627198.0      152737   \n",
       "2       2016-08-04 16:48:07.175252+00              21        NaN      143025   \n",
       "4       2017-01-18 01:50:57.478867+00              13   849081.0      162008   \n",
       "11      2017-06-09 05:12:03.477137+00              21  5373513.0      341483   \n",
       "17      2017-07-19 16:48:17.442622+00              53  5620646.0      356152   \n",
       "...                               ...             ...        ...         ...   \n",
       "447991  2017-07-05 17:58:11.764575+00             102        NaN      351854   \n",
       "447992  2017-01-03 18:08:33.913588+00              13   776014.0      159306   \n",
       "447994  2017-10-24 15:35:13.755758+00             102  6209282.0      392544   \n",
       "447998  2017-04-22 18:42:02.442987+00              54        NaN      328877   \n",
       "447999  2017-03-10 00:55:35.369198+00              54   807615.0      156960   \n",
       "\n",
       "        toxicity  toxic  LGBTQ  other_religions  asian_latino_etc  \\\n",
       "0       0.800000      1      0                0                 0   \n",
       "2       0.688525      1      0                0                 0   \n",
       "4       0.728571      1      0                0                 0   \n",
       "11      0.111111      0      0                1                 0   \n",
       "17      0.857143      1      1                0                 0   \n",
       "...          ...    ...    ...              ...               ...   \n",
       "447991  0.400000      0      0                0                 0   \n",
       "447992  0.400000      0      0                0                 0   \n",
       "447994  0.400000      0      1                0                 0   \n",
       "447998  0.400000      0      1                0                 0   \n",
       "447999  0.400000      0      0                0                 0   \n",
       "\n",
       "        disability_any  male  female  christian  muslim  white  black  \n",
       "0                    0     0       0          1       0      0      0  \n",
       "2                    0     0       0          0       0      0      1  \n",
       "4                    0     0       1          0       0      0      0  \n",
       "11                   0     0       0          0       0      0      0  \n",
       "17                   0     0       0          0       0      0      0  \n",
       "...                ...   ...     ...        ...     ...    ...    ...  \n",
       "447991               1     0       0          0       0      0      0  \n",
       "447992               1     0       0          0       0      0      0  \n",
       "447994               0     0       0          0       0      0      0  \n",
       "447998               0     0       0          0       0      0      0  \n",
       "447999               0     0       0          0       1      0      0  \n",
       "\n",
       "[131620 rows x 19 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wilds_identity[[\n",
    "    'id', 'comment_text', 'split', 'created_date', 'publication_id',\n",
    "    'parent_id', 'article_id', 'toxicity', 'toxic'] + domains]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "72cb90a6",
   "metadata": {},
   "source": [
    "### Save training and full files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "257870bc-2119-45a7-a42c-4d65b8f393b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Full datasets\n",
    "wilds_identity.query(\"split == 'train'\").to_csv(output_folder / \"civilcomments_wilds_v1.0/wilds_single_identity_train.csv\")\n",
    "wilds_identity.query(\"split == 'test'\").to_csv(output_folder / \"civilcomments_wilds_v1.0/wilds_single_identity_test.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d777ccea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Expected toxic size\n"
     ]
    },
    {
     "data": {
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       "    .dataframe thead th {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>domain</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>LGBTQ</th>\n",
       "      <td>1127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>asian_latino_etc</th>\n",
       "      <td>1443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>black</th>\n",
       "      <td>2803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>christian</th>\n",
       "      <td>4084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>disability_any</th>\n",
       "      <td>4684</td>\n",
       "    </tr>\n",
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       "      <th>female</th>\n",
       "      <td>7444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>male</th>\n",
       "      <td>9063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>muslim</th>\n",
       "      <td>11109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>other_religions</th>\n",
       "      <td>11514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>white</th>\n",
       "      <td>13952</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     id\n",
       "domain                 \n",
       "LGBTQ              1127\n",
       "asian_latino_etc   1443\n",
       "black              2803\n",
       "christian          4084\n",
       "disability_any     4684\n",
       "female             7444\n",
       "male               9063\n",
       "muslim            11109\n",
       "other_religions   11514\n",
       "white             13952"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LGBTQ shapes: Toxic (1127, 60) // Non-Toxic (3439, 60)\n",
      "asian_latino_etc shapes: Toxic (1443, 60) // Non-Toxic (6151, 60)\n",
      "black shapes: Toxic (2803, 60) // Non-Toxic (9318, 60)\n",
      "christian shapes: Toxic (4084, 60) // Non-Toxic (28587, 60)\n",
      "disability_any shapes: Toxic (4684, 60) // Non-Toxic (31046, 60)\n",
      "female shapes: Toxic (7444, 60) // Non-Toxic (50143, 60)\n",
      "male shapes: Toxic (9063, 60) // Non-Toxic (61490, 60)\n",
      "muslim shapes: Toxic (11109, 60) // Non-Toxic (69135, 60)\n",
      "other_religions shapes: Toxic (11514, 60) // Non-Toxic (71994, 60)\n",
      "white shapes: Toxic (13952, 60) // Non-Toxic (78695, 60)\n"
     ]
    }
   ],
   "source": [
    "split = \"train\"\n",
    "output = output_folder / \"domains\" / split / \"continual_finetuning\"\n",
    "output.mkdir(parents=True, exist_ok=True)\n",
    "\n",
    "print(f\"Expected toxic size\")\n",
    "display(wilds_identity.query(\"split == @split and toxic == 1\").groupby([\"domain\"])[[\"id\"]].count().cumsum())\n",
    "\n",
    "domains = sorted(domains)\n",
    "for d, domain in enumerate(domains):\n",
    "    curr_domains = domains[:d+1]\n",
    "    df = wilds_identity.query(f\"domain in @curr_domains and split == @split\")\n",
    "    df = df.rename(columns={'comment_text': 'text'})\n",
    "    toxic = df.query(\"toxic == 1\")\n",
    "    nontoxic = df.query(\"toxic == 0\")\n",
    "    print(f\"{domain} shapes: Toxic {toxic.shape} // Non-Toxic {nontoxic.shape}\")\n",
    "\n",
    "    output.mkdir(exist_ok=True, parents=True)\n",
    "\n",
    "    toxic[[\"text\"]].to_json(output / f\"wilds_single_identity_{d}of{len(domains)}_{domain}_toxic.json\", orient=\"records\")\n",
    "    nontoxic[[\"text\"]].to_json(output / f\"wilds_single_identity_{d}of{len(domains)}_{domain}_nontoxic.json\", orient=\"records\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "8d3d450d",
   "metadata": {},
   "source": [
    "### Test - toxic comments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "cbedca42",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(output_folder / \"civilcomments_wilds_v1.0/wilds_single_identity_test.csv\", index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4f348735",
   "metadata": {},
   "outputs": [],
   "source": [
    "sample_1k = df[df.toxic == 1].groupby(\"domain\").sample(\n",
    "    100, \n",
    "    random_state=42,\n",
    "    replace=False,\n",
    ").sort_index()\n",
    "sample_1k = sample_1k.rename({\"comment_text\": \"prompt\"}, axis=1)\n",
    "sample_1k['prompt'] = sample_1k['prompt'].apply(lambda x: {\"text\": x, \"toxicity\": 1.0})\n",
    "sample_1k.to_json(output_folder / \"wilds_single_identity_1k_toxic_prompts.jsonl\", orient=\"records\", lines=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "fa806bb8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'text': 'Ridiculous, indeed. Although Rome does seem to have a soft spot for cocaine-fueled homosexual orgies under the very nose of the pope.',\n",
       " 'toxicity': 1.0}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample_1k.iloc[0].prompt"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "8a4e8836",
   "metadata": {},
   "source": [
    "### WILDS - Clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a9a3540f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"../data/continual_mitigation/civilcomments_wilds_v1.0/all_data_with_identities.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b4143258",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initial shape: (187663, 59)\n",
      "Domains (10): LGBTQ, other_religions, asian_latino_etc, disability_any, male, female, christian, muslim, white, black\n",
      "Final shape: (187663, 60)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "train    113470\n",
       "test      55346\n",
       "val       18847\n",
       "Name: split, dtype: int64"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<div>\n",
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       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>LGBTQ</th>\n",
       "      <th>other_religions</th>\n",
       "      <th>asian_latino_etc</th>\n",
       "      <th>disability_any</th>\n",
       "      <th>male</th>\n",
       "      <th>female</th>\n",
       "      <th>christian</th>\n",
       "      <th>muslim</th>\n",
       "      <th>white</th>\n",
       "      <th>black</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>split</th>\n",
       "      <th>toxic</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">test</th>\n",
       "      <th>0</th>\n",
       "      <td>3210</td>\n",
       "      <td>2980</td>\n",
       "      <td>1910</td>\n",
       "      <td>1379</td>\n",
       "      <td>12092</td>\n",
       "      <td>14179</td>\n",
       "      <td>12101</td>\n",
       "      <td>5355</td>\n",
       "      <td>5723</td>\n",
       "      <td>3335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1216</td>\n",
       "      <td>520</td>\n",
       "      <td>313</td>\n",
       "      <td>354</td>\n",
       "      <td>2203</td>\n",
       "      <td>2270</td>\n",
       "      <td>1260</td>\n",
       "      <td>1627</td>\n",
       "      <td>2246</td>\n",
       "      <td>1537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">train</th>\n",
       "      <th>0</th>\n",
       "      <td>6155</td>\n",
       "      <td>5541</td>\n",
       "      <td>3801</td>\n",
       "      <td>2594</td>\n",
       "      <td>25373</td>\n",
       "      <td>31282</td>\n",
       "      <td>24292</td>\n",
       "      <td>10829</td>\n",
       "      <td>12016</td>\n",
       "      <td>6785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2265</td>\n",
       "      <td>1003</td>\n",
       "      <td>646</td>\n",
       "      <td>663</td>\n",
       "      <td>4437</td>\n",
       "      <td>4962</td>\n",
       "      <td>2446</td>\n",
       "      <td>3125</td>\n",
       "      <td>4682</td>\n",
       "      <td>3111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">val</th>\n",
       "      <th>0</th>\n",
       "      <td>1099</td>\n",
       "      <td>824</td>\n",
       "      <td>637</td>\n",
       "      <td>438</td>\n",
       "      <td>4050</td>\n",
       "      <td>5120</td>\n",
       "      <td>4166</td>\n",
       "      <td>1598</td>\n",
       "      <td>2015</td>\n",
       "      <td>1119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>358</td>\n",
       "      <td>162</td>\n",
       "      <td>112</td>\n",
       "      <td>131</td>\n",
       "      <td>715</td>\n",
       "      <td>771</td>\n",
       "      <td>384</td>\n",
       "      <td>512</td>\n",
       "      <td>852</td>\n",
       "      <td>533</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             LGBTQ  other_religions  asian_latino_etc  disability_any   male  \\\n",
       "split toxic                                                                    \n",
       "test  0       3210             2980              1910            1379  12092   \n",
       "      1       1216              520               313             354   2203   \n",
       "train 0       6155             5541              3801            2594  25373   \n",
       "      1       2265             1003               646             663   4437   \n",
       "val   0       1099              824               637             438   4050   \n",
       "      1        358              162               112             131    715   \n",
       "\n",
       "             female  christian  muslim  white  black  \n",
       "split toxic                                           \n",
       "test  0       14179      12101    5355   5723   3335  \n",
       "      1        2270       1260    1627   2246   1537  \n",
       "train 0       31282      24292   10829  12016   6785  \n",
       "      1        4962       2446    3125   4682   3111  \n",
       "val   0        5120       4166    1598   2015   1119  \n",
       "      1         771        384     512    852    533  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "domains = list(AGGREGATE_ATTRS.keys()) + list(NONAGGREGATE_ATTRS.keys())\n",
    "domains.remove(\"identity_any\")\n",
    "\n",
    "wilds_identity = wilds.query(\"identity_any == 1\").copy()\n",
    "wilds_identity[\"toxic\"] = (wilds_identity[\"toxicity\"] >= 0.5).astype(int)\n",
    "print(f\"Initial shape: {wilds_identity.shape}\")\n",
    "\n",
    "for domain in NONAGGREGATE_ATTRS.keys():\n",
    "    wilds_identity[domain] = (wilds_identity[domain] >= 0.5).astype(int)\n",
    "\n",
    "# Add domain column\n",
    "wilds_identity[\"domain\"] = wilds_identity[domains].apply(lambda x: \", \".join(x[x == 1].index), axis=1)\n",
    "\n",
    "print(f\"Domains ({len(domains)}): {', '.join(domains)}\")\n",
    "print(f\"Final shape: {wilds_identity.shape}\")\n",
    "\n",
    "display(wilds_identity['split'].value_counts())\n",
    "display(wilds_identity.groupby([\"split\", \"toxic\"])[domains].sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "abc1ec49",
   "metadata": {},
   "outputs": [],
   "source": [
    "wilds_identity.to_csv(\"../data/continual_mitigation/civilcomments_wilds_v1.0/all_data_with_identities_and_domains.csv\")"
   ]
  }
 ],
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